Data-centric declarative deep learning framework
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Updated
May 31, 2022 - Python
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Data-centric declarative deep learning framework
Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)
Deep diffs two objects, including nested structures of arrays and objects, and returns the difference.
A deep learning model for style-specific music generation.
Action recognition using soft attention based deep recurrent neural networks
JavaScript object detection lightweight library for augmented reality (WebXR demos included). It uses convolutional neural networks running on the GPU with WebGL.
Deep & Classical Reinforcement Learning + Machine Learning Examples in Python
Recursively (deep) clone JavaScript native types, like Object, Array, RegExp, Date as well as primitives. Used by superstruct, merge-deep, and many others!
High-performance immutable data structures for modern JavaScript and TypeScript applications. Functional interfaces, deep/composite operations API, mixed mutability API, TypeScript definitions, ES2015 module exports.
A professional deep clone library
Use property paths (`a.b.c`) get a nested value from an object.
Unsupervised Deep Homography: A Fast and Robust Homography Estimation Model
Reinforcement learning with tensorflow 2 keras
An isomorphic and configurable javascript utility for objects deep cloning that supports circular references.
Few Shot Learning by Siamese Networks, using Keras.
AI-based pathology predicts origins for cancers of unknown primary - Nature
Recursively merge values in a JavaScript object.
Code release for "3D-RelNet: Joint Object and Relation Network for 3D prediction"
Current implementations of CCA cannot handle data structures where one would expect structured covariance for certain variables (e.g. brain regions can be expected to covary the more close they are spatially, behavioral variables can be aggregated to certain groups like cognition, psychopathology, drugs, etc.). There have been two attempts to solve this problem: Group Sparse Canonical Correlation
Talk is cheap,show me the code ! Deep Learning,Leaning deep,Have fun!
YoloV3 in Pytorch and Jupyter Notebook
Deeply mix the properties of objects into the first object, while also mixing-in child objects.
Introspection for serializable arrays and JSON friendly objects.
DeepCShuffle should have feature parity with the base shuffle node. Interface should be same/identical.
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